Use Cases & Examples

Every example below is something you type to your connected assistant in plain language. The assistant picks the tools; the italic lines show the calls it makes under the hood.

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Start every session with your projects

Because almost every tool is project-scoped, the assistant resolves your project first.

You: What can you do with my Writesonic Agents account? Assistant calls whoami → returns your identity and projects, then works within the project you pick.

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Triage your task list

You: How many open tasks do I have, grouped by assignee? Assistant calls query_tasks with view: "counts" and group_by: "assignee_id".

You: Show me the high-priority tasks that aren’t done yet. Assistant calls query_tasks with view: "list" and a filter on priority and status.

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Create and manage a task

You: Create a task “Refresh the pricing page for AI search” and assign it to me. Assistant calls create_task, then update_task with action: "assign".

You: Move it to In Progress and add a comment with the target keywords. Assistant calls update_task (action: "transition_status") then comment_on_task.

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Follow the work an agent did

You: What did the agent do on task ABC-123? Walk me through the steps. Assistant calls get_agent_runs with task_id, then run_progress for the run to show each step.

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Inspect a playbook and its runs

You: List my content playbooks and show the last few runs of the blog one. Assistant calls list_workflows (view: "list"), then get_workflow (view: "runs") for the matching playbook.

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Read a grid

You: What columns are in my “Q3 landing pages” grid, and show the first 20 rows. Assistant calls list_grids to find it, then get_grid_data (view: "columns" then view: "rows").

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Search your knowledge and brand kit

You: What does our brand voice guide say about tone? Assistant calls get_brand_kit for the voice section, or search_knowledge across your sources.

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Pull a content-intelligence report

You: How is our /pricing page doing in AI citations this month? Assistant calls get_ci_dashboard (view: "pages") to resolve the page, then get_page_report with the AI-citations report_type.

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Chain several reads in one shot

For a multi-step question, the assistant can batch the calls instead of round-tripping each one.

You: Give me a status snapshot: open task counts, my three most recent playbook runs, and any failing integrations. Assistant uses execute_batch to run query_tasks, get_workflow (runs), and list_integrations in one request.

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Three things to take note of

• Name your project. Almost every tool is project-scoped, so the assistant resolves it with whoami first. Say which project you mean (“in my Acme project…”) and it won’t have to stop and ask.
• Writes always confirm first. Only create_task, update_task, and comment_on_task change anything, everything else is read-only. The assistant shows you the change and asks before writing, and each write is reversible in the product.
• Batch multi-step questions. For a question that needs several reads, ask for the whole thing in one message. The assistant chains the calls with execute_batch (or execute_plan when there are loops or conditionals) instead of round-tripping each one.

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Where to go next